Large-Scale Geo-Data Mining for Good

Abstract

The ever-increasing amount of earth observation data provides us an ample basis to sense, understand, and visualize the health of our planet. Machine learning enables us to value our home through mining massive amounts of geo-information provided by satellites and airborne measurements once curated for scalable access by a Big Geospatial Data "digital twin" platform. My presentation intends to bridge the "AI Ethics" to the "Big Data & Global Human Behavior" session through a technical overview of remote sensor technologies demonstrating their value for applications in archaeology, urban mapping, and biomass estimation relevant to various ethical aspects. I invite you to enter a vital, interdisciplinary discussion on a. How to leverage machine learning and remote sensing to improve the local climate in (mega)cities for the well-being of its urban population; and how to address ethical concerns related? b. How artificial intelligence and earth observation have the capacity to help protect the Amazon rainforest led by fair principles incorporating the "perspectives of all stakeholders" such as endangered species, local farmers, archaeologists, and governments? What are the current limitations of these technologies vis-a-vis protection of human rights and ethics; and how do we overcome limitations? c. How do we transparently implement AI-based environmental management inspired by the United Nation's Sustainable Development Goals?